Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 677 724 686 859 877 133 1000 52 989 892 105 618 846 502 302 69 393 818 193 416
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 193 NA 989 677 105 818 133 302 724 NA 502 416 859 686 1000 846 NA 69 52 877
[21] 618 892 393
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 4 4 5 1 3 2 4 4 4 3
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "b" "u" "k" "q" "g" "Y" "X" "V" "F" "T"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 7 9
which( manyNumbersWithNA > 900 )
[1] 3 15
which( is.na( manyNumbersWithNA ) )
[1] 2 10 17
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 1000 989
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 1000 989
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 1000 989
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "Y" "X" "V" "F" "T"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "b" "u" "k" "q" "g"
manyNumbers %in% 300:600
[1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE
[18] FALSE FALSE TRUE
which( manyNumbers %in% 300:600 )
[1] 14 15 17 20
sum( manyNumbers %in% 300:600 )
[1] 4
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "small" NA "large" "large" "small" "large" "small" "small" "large" NA "large" "small" "large"
[14] "large" "large" "large" NA "small" "small" "large" "large" "large" "small"
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "small" "UNKNOWN" "large" "large" "small" "large" "small" "small" "large" "UNKNOWN"
[11] "large" "small" "large" "large" "large" "large" "UNKNOWN" "small" "small" "large"
[21] "large" "large" "small"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 0 NA 989 677 0 818 0 0 724 NA 502 0 859 686 1000 846 NA 0 0 877
[21] 618 892 0
unique( duplicatedNumbers )
[1] 4 5 1 3 2
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 4 5 1 3 2
duplicated( duplicatedNumbers )
[1] FALSE TRUE FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE
which.max( manyNumbersWithNA )
[1] 15
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 1000
which.min( manyNumbersWithNA )
[1] 19
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 52
range( manyNumbersWithNA, na.rm = TRUE )
[1] 52 1000
manyNumbersWithNA
[1] 193 NA 989 677 105 818 133 302 724 NA 502 416 859 686 1000 846 NA 69 52 877
[21] 618 892 393
sort( manyNumbersWithNA )
[1] 52 69 105 133 193 302 393 416 502 618 677 686 724 818 846 859 877 892 989 1000
sort( manyNumbersWithNA, na.last = TRUE )
[1] 52 69 105 133 193 302 393 416 502 618 677 686 724 818 846 859 877 892 989 1000
[21] NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 1000 989 892 877 859 846 818 724 686 677 618 502 416 393 302 193 133 105 69 52
[21] NA NA NA
manyNumbersWithNA[1:5]
[1] 193 NA 989 677 105
order( manyNumbersWithNA[1:5] )
[1] 5 1 4 3 2
rank( manyNumbersWithNA[1:5] )
[1] 2 5 4 3 1
sort( mixedLetters )
[1] "b" "F" "g" "k" "q" "T" "u" "V" "X" "Y"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 4.5 7.0 9.0 9.0 6.0 9.0 2.5 1.0 2.5 4.5
rank( manyDuplicates, ties.method = "min" )
[1] 4 7 8 8 6 8 2 1 2 4
rank( manyDuplicates, ties.method = "random" )
[1] 5 7 9 8 6 10 3 1 2 4
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.00000000 -0.50000000 0.00000000 0.50000000 1.00000000 0.42724316 1.04802313 1.18628196
[9] 1.48550990 -0.82549720 -0.15091809 -0.04325337 -0.32946535 -0.83780534 -0.14797026
round( v, 0 )
[1] -1 0 0 0 1 0 1 1 1 -1 0 0 0 -1 0
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 0.4 1.0 1.2 1.5 -0.8 -0.2 0.0 -0.3 -0.8 -0.1
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 0.43 1.05 1.19 1.49 -0.83 -0.15 -0.04 -0.33 -0.84 -0.15
floor( v )
[1] -1 -1 0 0 1 0 1 1 1 -1 -1 -1 -1 -1 -1
ceiling( v )
[1] -1 0 0 1 1 1 2 2 2 0 0 0 0 0 0
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 x 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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